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Revert "add workflow to rebase with upstream main nightly."
yuyanpeng-google
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Add sharding
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* flux2-klein * Apply suggestions from code review Co-authored-by: Sayak Paul <spsayakpaul@gmail.com> * Klein tests (#2) * tests * up * tests * up * support step-distilled * Apply suggestions from code review Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com> * Apply suggestions from code review Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com> * doc string etc * style * more * copies * klein lora training scripts (#3) * initial commit * initial commit * remove remote text encoder * initial commit * initial commit * initial commit * revert * img2img fix * text encoder + tokenizer * text encoder + tokenizer * update readme * guidance * guidance * guidance * test * test * revert changes not needed for the non klein model * Update examples/dreambooth/train_dreambooth_lora_flux2_klein.py Co-authored-by: Sayak Paul <spsayakpaul@gmail.com> * fix guidance * fix validation * fix validation * fix validation * fix path * space --------- Co-authored-by: Sayak Paul <spsayakpaul@gmail.com> * style * Update src/diffusers/pipelines/flux2/pipeline_flux2_klein.py * Apply style fixes * auto pipeline --------- Co-authored-by: Sayak Paul <spsayakpaul@gmail.com> Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com> Co-authored-by: Linoy Tsaban <57615435+linoytsaban@users.noreply.github.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
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Enderfga
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Finding huggingface#1 — attention_kwargs plumbing: Both transformers now decorate forward() with @apply_lora_scale('attention_kwargs') (matches Wan); pipelines forward attention_kwargs to the transformer + encode_kv_cache, and the unused parameter is dropped from the inner _forward_train / _forward_cache / _forward_inference signatures. Pipeline docstrings updated to the standard wording. Finding huggingface#2 — naming: Rename far_cfg -> layout_cfg in the bidi transformer (the bidi path is not FAR; the FAR transformer keeps far_cfg, which is accurate there). Finding huggingface#3 — scheduler state machine: Add _step_index, _begin_index, step_index property, begin_index property, set_begin_index(), _init_step_index(). step() lazily initializes and advances the counter so downstream callbacks / composable schedulers can observe rollout progress. Sigma resolution remains a pure function of (timestep, r_timestep) — calling step() twice with identical args still returns identical prev_sample (idempotent). Finding huggingface#4 — redundant @torch.no_grad(): Drop the redundant decorators on bidi pipeline's encode_video and FAR pipeline's encode_kv_cache (callers are already in __call__'s no-grad scope). Finding huggingface#5 — dead code: Remove the unreachable temb.ndim == 2 else branch from the bidi transformer's output-norm path (condition_embedder.forward always returns a 3D temb). Finding huggingface#6 — private rename: forward_far_patchify[_inference] -> _forward_far_patchify[_inference] (only called internally by _forward_train / _forward_cache / _forward_inference). Finding huggingface#7 — pipeline comment numbering: Bidi + FAR pipelines renumber steps so the # 4. slot is no longer skipped. Finding huggingface#8 — mask-mod comment numbering: _build_causal_mask numbered comments now run 1) 2) 3) ... (was 1) 3) 4) ...). Tests: - New test_step_index_advances + test_set_begin_index_anchors_step_index in the scheduler test file exercise the new state machine. - All existing pipeline / transformer / scheduler tests still pass (85 passed, 85 skipped on CPU). Bit-exact: 8-step rollout vs the previous formulation, max abs diff = 0.0 (the new sigma-lookup is byte-identical to t/num_train_timesteps on this schedule).
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